Title :
Estimation of a signal waveform from noisy data using low-rank approximation to a data matrix
Author :
Tufts, Donald W. ; Shah, Abhijit A.
Author_Institution :
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
fDate :
4/1/1993 12:00:00 AM
Abstract :
An analysis and improvement of a data-adaptive signal estimation algorithm are presented. Perturbation analysis of a reduced-rank data matrix is used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration algorithm of D. Tufts et al. (1982). This analysis leads to improvements of the methods, and the predicted improvements are demonstrated by simulation and comparison with the Cramer-Rao bounds
Keywords :
approximation theory; matrix algebra; noise; signal processing; waveform analysis; Toeplitz-restoration algorithm; data matrix; data-adaptive signal estimation algorithm; low-rank approximation; noisy data; perturbation analysis; signal waveform estimation; simulation; statistical properties; Autocorrelation; Cities and towns; Entropy; Equations; Information theory; Lattices; Linear systems; Predictive models; Signal processing algorithms; Spectral analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
